Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approach

<p>Abstract</p> <p>Background</p> <p>Alzheimer’s disease (AD) is the most frequently diagnosed neurodegenerative disorder affecting humans, with advanced age being the most prominent risk factor for developing AD. Despite intense research efforts aimed at elucidating th...

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Main Authors: Proctor Carole J, Pienaar Ilse, Elson Joanna L, Kirkwood Thomas BL
Format: Article
Language:English
Published: BMC 2012-07-01
Series:Molecular Neurodegeneration
Subjects:
Online Access:http://www.molecularneurodegeneration.com/content/7/1/32
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author Proctor Carole J
Pienaar Ilse
Elson Joanna L
Kirkwood Thomas BL
author_facet Proctor Carole J
Pienaar Ilse
Elson Joanna L
Kirkwood Thomas BL
author_sort Proctor Carole J
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>Alzheimer’s disease (AD) is the most frequently diagnosed neurodegenerative disorder affecting humans, with advanced age being the most prominent risk factor for developing AD. Despite intense research efforts aimed at elucidating the precise molecular underpinnings of AD, a definitive answer is still lacking. In recent years, consensus has grown that dimerisation of the polypeptide amyloid-beta (Aß), particularly Aß<sub>42</sub>, plays a crucial role in the neuropathology that characterise AD-affected post-mortem brains, including the large-scale accumulation of fibrils, also referred to as senile plaques. This has led to the realistic hope that targeting Aß<sub>42</sub> immunotherapeutically could drastically reduce plaque burden in the ageing brain, thus delaying AD onset or symptom progression. Stochastic modelling is a useful tool for increasing understanding of the processes underlying complex systems-affecting disorders such as AD, providing a rapid and inexpensive strategy for testing putative new therapies. In light of the tool’s utility, we developed computer simulation models to examine Aß<sub>42</sub> turnover and its aggregation in detail and to test the effect of immunization against Aß dimers.</p> <p>Results</p> <p>Our model demonstrates for the first time that even a slight decrease in the clearance rate of Aß<sub>42</sub> monomers is sufficient to increase the chance of dimers forming, which could act as instigators of protofibril and fibril formation, resulting in increased plaque levels. As the process is slow and levels of Aβ are normally low, stochastic effects are important. Our model predicts that reducing the rate of dimerisation leads to a significant reduction in plaque levels and delays onset of plaque formation. The model was used to test the effect of an antibody mediated immunological response. Our results showed that plaque levels were reduced compared to conditions where antibodies are not present.</p> <p>Conclusion</p> <p>Our model supports the current thinking that levels of dimers are important in initiating the aggregation process. Although substantial knowledge exists regarding the process, no therapeutic intervention is on offer that reliably decreases disease burden in AD patients. Computer modelling could serve as one of a number of tools to examine both the validity of reliable biomarkers and aid the discovery of successful intervention strategies.</p>
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spelling doaj.art-49209523d77e44f3a11a343619214f342022-12-22T00:10:42ZengBMCMolecular Neurodegeneration1750-13262012-07-01713210.1186/1750-1326-7-32Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approachProctor Carole JPienaar IlseElson Joanna LKirkwood Thomas BL<p>Abstract</p> <p>Background</p> <p>Alzheimer’s disease (AD) is the most frequently diagnosed neurodegenerative disorder affecting humans, with advanced age being the most prominent risk factor for developing AD. Despite intense research efforts aimed at elucidating the precise molecular underpinnings of AD, a definitive answer is still lacking. In recent years, consensus has grown that dimerisation of the polypeptide amyloid-beta (Aß), particularly Aß<sub>42</sub>, plays a crucial role in the neuropathology that characterise AD-affected post-mortem brains, including the large-scale accumulation of fibrils, also referred to as senile plaques. This has led to the realistic hope that targeting Aß<sub>42</sub> immunotherapeutically could drastically reduce plaque burden in the ageing brain, thus delaying AD onset or symptom progression. Stochastic modelling is a useful tool for increasing understanding of the processes underlying complex systems-affecting disorders such as AD, providing a rapid and inexpensive strategy for testing putative new therapies. In light of the tool’s utility, we developed computer simulation models to examine Aß<sub>42</sub> turnover and its aggregation in detail and to test the effect of immunization against Aß dimers.</p> <p>Results</p> <p>Our model demonstrates for the first time that even a slight decrease in the clearance rate of Aß<sub>42</sub> monomers is sufficient to increase the chance of dimers forming, which could act as instigators of protofibril and fibril formation, resulting in increased plaque levels. As the process is slow and levels of Aβ are normally low, stochastic effects are important. Our model predicts that reducing the rate of dimerisation leads to a significant reduction in plaque levels and delays onset of plaque formation. The model was used to test the effect of an antibody mediated immunological response. Our results showed that plaque levels were reduced compared to conditions where antibodies are not present.</p> <p>Conclusion</p> <p>Our model supports the current thinking that levels of dimers are important in initiating the aggregation process. Although substantial knowledge exists regarding the process, no therapeutic intervention is on offer that reliably decreases disease burden in AD patients. Computer modelling could serve as one of a number of tools to examine both the validity of reliable biomarkers and aid the discovery of successful intervention strategies.</p>http://www.molecularneurodegeneration.com/content/7/1/32Alzheimer’s diseaseAmyloid-betaDimersDown’s syndromeInterventionImmunotherapyMathematical modelProtein aggregationStochastic simulation
spellingShingle Proctor Carole J
Pienaar Ilse
Elson Joanna L
Kirkwood Thomas BL
Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approach
Molecular Neurodegeneration
Alzheimer’s disease
Amyloid-beta
Dimers
Down’s syndrome
Intervention
Immunotherapy
Mathematical model
Protein aggregation
Stochastic simulation
title Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approach
title_full Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approach
title_fullStr Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approach
title_full_unstemmed Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approach
title_short Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approach
title_sort aggregation impaired degradation and immunization targeting of amyloid beta dimers in alzheimer s disease a stochastic modelling approach
topic Alzheimer’s disease
Amyloid-beta
Dimers
Down’s syndrome
Intervention
Immunotherapy
Mathematical model
Protein aggregation
Stochastic simulation
url http://www.molecularneurodegeneration.com/content/7/1/32
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